Economics, agenda, and open questions
The cost case for owning versus renting, a twelve month agenda, and an honest account of what we may be wrong about. Part V of the Sovereignty Series.
The question is not whether to use AI. It is who accumulates the value of using it.
The closing part sets out the economics, a practical twelve month agenda, and the arguments against our own position.
7. The economics of owning versus renting
| Component | Favors |
|---|---|
| Accumulated institutional value | Owning, strongly |
| Switching cost over time | Owning, strongly |
| Deprecation cost predictability | Owning, moderately |
| Direct cost at enterprise scale | Owning, moderately |
| Security and key person risk | Renting, moderately |
| Operating burden and reliability | Renting, strongly |
If your competitive advantage is the accumulated judgment of your people, then the layer where that judgment is expressed is not a commodity, and you should not rent it.
8. A twelve month agenda
| Workstream | Timing | What it means |
|---|---|---|
| See | Q1 | Run the six-layer diagnostic honestly, including a shadow AI estimate. Instrument before you procure. |
| Decide the boundary | Q1–Q2 | Write down which layers are rented and which are owned. A governance decision, made once and defended. |
| Build the knowledge substrate | Q2 | Convert high-value institutional knowledge into structured, versioned text inside the retrieval path. |
| Agent registry and capability rule | Q2–Q3 | Portable definitions and lifecycle, before the agent population reaches the hundreds. |
| Abstract the model | Q3 | Governed routing validated with a real regression run. |
| Join telemetry to the P&L | Q3–Q4 | Correlate usage with margin, win rate and delivery. Retire adoption as the headline metric. |
| Fund the champion network | Continuous | Organizational readiness accounts for roughly twice the AI impact of individual readiness. |
9. What we may be wrong about
- Frontier providers may absorb the layer. If they ship enterprise-grade knowledge graphs, portable agent registries and full telemetry export as commodity features, the differentiated value of an owned layer narrows.
- Open standards may make the question moot. If MCP, A2A and their successors mature sufficiently, portability becomes a property of the ecosystem rather than an achievement of the enterprise.
- Enterprise behavior contradicts the thesis. Buyers chose dependency with full information; the competing explanation is that they rationally value support, indemnification and provenance over portability.
- Our own case study does not yet close the loop. We have argued ownership makes P&L attribution possible, and we have not yet published one.
10. Conclusion
The intelligence layer is the most consequential architectural decision most enterprises will make this decade, and the majority are making it by default, one seat license at a time. None of the four forces requires a provider to behave badly. It only requires the market to keep behaving as it currently does.
Against that, the enterprise has one durable advantage no provider can replicate: it is the only party that has its own institution. That asset either compounds inside a boundary the enterprise controls, or it accrues, interaction by interaction, to someone else. Michael Baker built Titan because we concluded that an engineering firm whose entire value proposition is accumulated technical judgment cannot rationally rent the layer in which that judgment is now expressed. The build was harder than we expected, we sequenced part of it wrong, and we would do it again.
In five years, when your most experienced people have retired and your systems answer questions in their place, who will own the thing that learned from them?
Notes on method
Figures are drawn from primary sources wherever available, with publication dates given so readers can assess currency in a market that moves quarterly. Principal sources: Menlo Ventures, 2025: The State of Generative AI in the Enterprise (Dec 2025); McKinsey, The state of AI in 2025 (Nov 2025, n=1,993); BCG CEO survey (Jul 2026, n=152); Microsoft Work Trend Index 2026 (May 2026, n=20,000); BST Global & ACEC, AI + Data Insights 2026 (May 2026); Stanford HAI, AI Index Report 2026; Gartner, Top Trends for Data and Analytics 2026; and provider pricing and deprecation documentation retrieved 7 August 2026. Framework exhibits are qualitative illustrations of the argument and should not be cited as measurements.